Uses of Class
org.tensorflow.framework.OptimizerOptions.Builder
Packages that use OptimizerOptions.Builder
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Uses of OptimizerOptions.Builder in org.tensorflow.framework
Methods in org.tensorflow.framework that return OptimizerOptions.BuilderModifier and TypeMethodDescriptionOptimizerOptions.Builder.addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) OptimizerOptions.Builder.clear()OptimizerOptions.Builder.clearCpuGlobalJit()CPU code will be autoclustered only if global_jit_level >= ON_1 and either: - this flag is true, or - TF_XLA_FLAGS contains --tf_xla_cpu_global_jit=true.OptimizerOptions.Builder.clearDoCommonSubexpressionElimination()If true, optimize the graph using common subexpression elimination.OptimizerOptions.Builder.clearDoConstantFolding()If true, perform constant folding optimization on the graph.OptimizerOptions.Builder.clearDoFunctionInlining()If true, perform function inlining on the graph.OptimizerOptions.Builder.clearField(com.google.protobuf.Descriptors.FieldDescriptor field) OptimizerOptions.Builder.clearGlobalJitLevel().tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;OptimizerOptions.Builder.clearMaxFoldedConstantInBytes()Constant folding optimization replaces tensors whose values can be predetermined, with constant nodes.OptimizerOptions.Builder.clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) OptimizerOptions.Builder.clearOptLevel()Overall optimization level.OptimizerOptions.Builder.clone()GraphOptions.Builder.getOptimizerOptionsBuilder()Options controlling how graph is optimized.OptimizerOptions.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) OptimizerOptions.Builder.mergeFrom(com.google.protobuf.Message other) OptimizerOptions.Builder.mergeFrom(OptimizerOptions other) final OptimizerOptions.BuilderOptimizerOptions.Builder.mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) static OptimizerOptions.BuilderOptimizerOptions.newBuilder()static OptimizerOptions.BuilderOptimizerOptions.newBuilder(OptimizerOptions prototype) OptimizerOptions.newBuilderForType()protected OptimizerOptions.BuilderOptimizerOptions.newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) OptimizerOptions.Builder.setCpuGlobalJit(boolean value) CPU code will be autoclustered only if global_jit_level >= ON_1 and either: - this flag is true, or - TF_XLA_FLAGS contains --tf_xla_cpu_global_jit=true.OptimizerOptions.Builder.setDoCommonSubexpressionElimination(boolean value) If true, optimize the graph using common subexpression elimination.OptimizerOptions.Builder.setDoConstantFolding(boolean value) If true, perform constant folding optimization on the graph.OptimizerOptions.Builder.setDoFunctionInlining(boolean value) If true, perform function inlining on the graph.OptimizerOptions.Builder.setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) OptimizerOptions.Builder.setGlobalJitLevel(OptimizerOptions.GlobalJitLevel value) .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;OptimizerOptions.Builder.setGlobalJitLevelValue(int value) .tensorflow.OptimizerOptions.GlobalJitLevel global_jit_level = 5;OptimizerOptions.Builder.setMaxFoldedConstantInBytes(long value) Constant folding optimization replaces tensors whose values can be predetermined, with constant nodes.OptimizerOptions.Builder.setOptLevel(OptimizerOptions.Level value) Overall optimization level.OptimizerOptions.Builder.setOptLevelValue(int value) Overall optimization level.OptimizerOptions.Builder.setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value) final OptimizerOptions.BuilderOptimizerOptions.Builder.setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) OptimizerOptions.toBuilder()Methods in org.tensorflow.framework with parameters of type OptimizerOptions.BuilderModifier and TypeMethodDescriptionGraphOptions.Builder.setOptimizerOptions(OptimizerOptions.Builder builderForValue) Options controlling how graph is optimized.